""" 自动反思与验证服务 用于记录分析预测，并在未来自动验证结果，实现闭环学习 """ import sqlite3 import os import json from datetime import datetime, timedelta from typing import List, Dict, Any, Optional from app.utils.logger import get_logger from .memory import AgentMemory from .tools import AgentTools logger = get_logger(__name__) class ReflectionService: """反思服务：管理分析记录的存储和验证""" def __init__(self, db_path: Optional[str] = None): if db_path is None: # 默认数据库路径 db_dir = os.path.join(os.path.dirname(__file__), '..', '..', '..', 'data', 'memory') os.makedirs(db_dir, exist_ok=True) db_path = os.path.join(db_dir, 'reflection_records.db') self.db_path = db_path self.tools = AgentTools() self._init_database() def _init_database(self): """初始化数据库表""" try: conn = sqlite3.connect(self.db_path) cursor = conn.cursor() # 创建分析记录表 cursor.execute(''' CREATE TABLE IF NOT EXISTS analysis_records ( id INTEGER PRIMARY KEY AUTOINCREMENT, market TEXT NOT NULL, symbol TEXT NOT NULL, initial_price REAL, decision TEXT, confidence INTEGER, reasoning TEXT, analysis_date TIMESTAMP DEFAULT CURRENT_TIMESTAMP, target_check_date TIMESTAMP, status TEXT DEFAULT 'PENDING', -- PENDING, COMPLETED, FAILED final_price REAL, actual_return REAL, check_result TEXT ) ''') # 创建索引 cursor.execute(''' CREATE INDEX IF NOT EXISTS idx_status_date ON analysis_records(status, target_check_date) ''') conn.commit() conn.close() except Exception as e: logger.error(f"初始化反思数据库失败: {e}") def record_analysis(self, market: str, symbol: str, price: float, decision: str, confidence: int, reasoning: str, check_days: int = 7): """ 记录一次分析，以便未来验证 Args: market: 市场 symbol: 代码 price: 当前价格 decision: 决策 (BUY/SELL/HOLD) confidence: 置信度 reasoning: 理由 check_days: 几天后验证 (默认7天) """ try: conn = sqlite3.connect(self.db_path) cursor = conn.cursor() target_date = datetime.now() + timedelta(days=check_days) cursor.execute(''' INSERT INTO analysis_records (market, symbol, initial_price, decision, confidence, reasoning, target_check_date) VALUES (?, ?, ?, ?, ?, ?, ?) ''', (market, symbol, price, decision, confidence, reasoning, target_date)) conn.commit() conn.close() logger.info(f"Recorded analysis for reflection: {market}:{symbol}, will verify after {check_days} day(s)") except Exception as e: logger.error(f"记录分析失败: {e}") def run_verification_cycle(self): """ 执行验证周期：检查到期的记录，验证结果，并写入记忆 """ logger.info("开始执行自动反思验证周期...") try: conn = sqlite3.connect(self.db_path) cursor = conn.cursor() # 1. 查找所有已到期且未处理的记录 cursor.execute(''' SELECT id, market, symbol, initial_price, decision, confidence, reasoning, analysis_date FROM analysis_records WHERE status = 'PENDING' AND target_check_date <= CURRENT_TIMESTAMP ''') records = cursor.fetchall() if not records: logger.info("没有需要验证的记录") conn.close() return logger.info(f"发现 {len(records)} 条待验证记录") # 初始化记忆系统（用于写入验证结果） trader_memory = AgentMemory('trader_agent') for record in records: record_id, market, symbol, initial_price, decision, confidence, reasoning, analysis_date = record try: # 2. 获取当前最新价格 current_price_data = self.tools.get_current_price(market, symbol) current_price = current_price_data.get('price') if not current_price: logger.warning(f"无法获取 {market}:{symbol} 的当前价格，跳过") continue # 3. 计算收益和结果 if not initial_price or initial_price == 0: actual_return = 0.0 else: actual_return = (current_price - initial_price) / initial_price * 100 # 评估结果 result_desc = "" is_good_prediction = False if decision == "BUY": if actual_return > 2.0: result_desc = "Correct: price rose after BUY" is_good_prediction = True elif actual_return < -2.0: result_desc = "Wrong: price fell after BUY" else: result_desc = "Neutral: limited price movement" elif decision == "SELL": if actual_return < -2.0: result_desc = "Correct: price fell after SELL" is_good_prediction = True elif actual_return > 2.0: result_desc = "Wrong: price rose after SELL" else: result_desc = "Neutral: limited price movement" else: # HOLD if -2.0 <= actual_return <= 2.0: result_desc = "Correct: limited movement during HOLD" is_good_prediction = True else: result_desc = f"Deviated: large movement during HOLD ({actual_return:.2f}%)" # 4. 写入记忆系统 (Let the agent learn) memory_situation = f"{market}:{symbol} auto-verified (analysis_date: {analysis_date})" memory_recommendation = f"Decision: {decision} (confidence {confidence}), reasoning: {(reasoning or '')[:120]}" memory_result = f"Verification: {result_desc}; return={actual_return:.2f}% (initial {initial_price} -> final {current_price})" trader_memory.add_memory( memory_situation, memory_recommendation, memory_result, actual_return, metadata={ "market": market, "symbol": symbol, "timeframe": "1D", "features": { "source": "auto_verify", "decision": decision, "confidence": confidence, "initial_price": initial_price, "final_price": current_price, "analysis_date": str(analysis_date), "result_desc": result_desc, "is_good_prediction": bool(is_good_prediction), }, } ) # 5. 更新记录状态 cursor.execute(''' UPDATE analysis_records SET status = 'COMPLETED', final_price = ?, actual_return = ?, check_result = ? WHERE id = ? ''', (current_price, actual_return, result_desc, record_id)) conn.commit() logger.info(f"验证完成 {market}:{symbol}: {result_desc}") except Exception as inner_e: logger.error(f"处理记录 {record_id} 失败: {inner_e}") # 标记为失败，避免重复处理 # cursor.execute("UPDATE analysis_records SET status = 'FAILED' WHERE id = ?", (record_id,)) # conn.commit() conn.close() logger.info("反思验证周期结束") except Exception as e: logger.error(f"执行验证周期失败: {e}")